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$SOUN On Breakout WatchlistNASDAQ:SOUN is an AI stock that has not gotten much love as with other AI themed issues. Maybe one reason the market has been ignoring it is that has yet to make a profit. However, they are in the AI voice response business which cuts across many industries. While I think they have a bright and disruptive type future, it is the market’s opinion that matters. You can see my notes on the chart. There are two merging resistance areas, the IPO AVWAP and resistance area since March. I have an alert set at $3.40. If it can get above and hold this may have room to run. This is the kind of stock that could easily double or triple in a short period of time. All TBD. Thanks for looking. I hope this helps someone. Constructive comments always welcome.
NASDAQ:SOUN
by jaxdog
Will AI workloads consume all the world’s energy?On big questions like this, almost nothing stays constant. When we consider a new technology: We cannot assume that rates of adoption or usage will remain constant—they may drop, they may even grow. We cannot assume that the technology supplying our energy needs will remain constant—there could be breakthroughs in efficiency or changes in the overall energy mix. We cannot assume that the efficiency of the specific technology being adopted will remain constant—we have seen numerous examples of areas where an initial version of something in technology or software faces subsequent improvements that may give it greater capabilities with lower energy usage. We must also recognise that artificial intelligence (AI) itself could suggest improvements in energy efficiency for specific applications—like the heating and cooling of a building. Therefore, any analysis of energy usage and AI must recognise that the one constant will be change. Environmental impact of select large language models (LLMs) LLMs have been garnering the lion’s share of attention amidst the current excitement around generative AI. It makes sense to consider the amount of carbon emissions generated by some of these systems. The Stanford AI Index Report, published in 2023, provided some data, noting that factors like the number of parameters in a model, the power usage effectiveness1 of a data centre, and the grid carbon intensity all matter. Considering power consumption of an LLM Those building different LLMs have many levers they can pull in order to influence different characteristics, like energy consumption. Google researchers proposed a family of language models named GLaM (Generalist Language Model), which uses a ‘sparsely activated mixture of experts’. While a full discussion of how that type of approach works is beyond the scope of this piece, we note that the largest of the GLaM models has 1.2 trillion parameters. Knowing solely that data point, the assumption would be that this model would consume more energy than any of the models. In reality, the GLaM model with 1.2 trillion parameters consumes only one-third of the energy required to train GPT-3 and requires only half of the computation flops for inference operations. A simple way to think of what is going on is that, while the total model has 1.2 trillion parameters, a given input token into the GLaM model is only activating a maximum of 95 billion parameters, that is, the entire model isn’t active across all the parameters. GPT-3, on the other hand, activated all 175 billion parameters on each input token3. It is notable that, even if measuring the performance of AI models occurs on many dimensions, by many measures the GLaM model is able to outperform GPT-3 as well4. Conclusion The bottom line is that model design matters, and if model designers want to denote ways to maintain performance but use less energy, they have many options. Sources 1 Power usage effectiveness (PUE) is useful in evaluating the energy efficiency of data centres in a standard way. PUE = (total amount of energy used by a computer data centre facility) / (energy delivered to computer equipment). A higher PUE means that the data centre is less efficient. 2 Source: Du et al. “GLaM: Efficient Scaling of Language Models with Mixture-of-Experts.” ARXIV.org. 1 August 2022. 3 Source: Patterson, David; Gonzalez, Joseph; Hölzle, Urs; Le, Quoc Hung; Liang, Chen; Munguia, Lluis-Miquel; et al. (2022): The Carbon Footprint of Machine Learning Training Will Plateau, Then Shrink. TechRxiv. 4 Source: Du et al, 1 August 2022.
Editors' picks
SPARKS:AIX
by aneekaguptaWTE
9
Bitcoin Forecast Cloudy☁️ (Clear: 0.0 %)🌥️ Bitcoin Weather Forecast Analysis 🌥️ Based on the recent Bitcoin chart index for the past hour, it appears that the weather in the Bitcoin world is forecasted to be cloudy. As an investment chartist, I have assessed the current market conditions and unfortunately, my confidence in the Bitcoin market being sunny is extremely low, scoring 0 on a scale of 0 to 1. This score falls below the baseline confidence level of 0.864. Taking a closer look at the chart index, here are the key observations: - Open: 25007 - High: 25028 - Low: 24911 - Volume: 17028 - Close: 24944 - ema9: 24994 - ema21: 25181 - ema50: 25479 - ema100: 25686 - ema200: 25847 - rsi: 33 - fast_k: 40 - slow_k: 34 - slow_d: 26 - macd: -412 The presence of a "dead cat bounce" pattern, which typically indicates a temporary recovery before resuming a downward trend, is noticeable in the market. However, it seems that the power of this dead cat bounce is diminishing briefly. The low confidence score can be attributed to several factors. The price action shows a decreasing trend, with the current Close at 24944 being lower than the Open. Additionally, the exponential moving averages (ema9, ema21, ema50, ema100, and ema200) suggest a bearish sentiment as they are trending downwards, indicating a negative momentum in the Bitcoin market. Furthermore, the relative strength index (RSI) is at 33, which is relatively low and indicates a potential oversold condition. The fast_k and slow_k indicators are also relatively low at 40 and 34, respectively, further supporting the bearish sentiment. The slow_d value of 26 indicates a weakening momentum in the market. Lastly, the moving average convergence divergence (MACD) is -412, indicating a strong bearish signal. Considering all these factors, the overall market conditions point towards a cloudy outlook for Bitcoin in the near term. Traders and investors should exercise caution and closely monitor the market for any potential shifts in the weather.
BINANCE:BTCUSD
by ChatGPT_Bitcoin_Forecaster
Bitcoin Forecast Sunny🌞 (Clear: 100.0 %)🌤️ Bitcoin Weather Report: Sunny Forecast! 🌤️ According to the latest Bitcoin chart index for the past hour, I'm happy to announce that the weather in the Bitcoin world is expected to be sunny ☀️. With a confidence level of 1.0, I have high certainty in this forecast. Let's take a closer look at the key indicators: 📈 Open: 25019 🔼 High: 25063 🔽 Low: 24890 📊 Volume: 18820 📉 Close: 24918 The recent price movement indicates a potential for a dead cat bounce 🐱 following a sharp drop. This means that after a significant decline, there might be a short-lived upward movement before the downward trend resumes. However, it's important to approach this with caution as dead cat bounces are typically temporary and may not signal a sustained recovery. Moving on to the moving averages, we observe the following values: 📈 EMA9: 25101 📈 EMA21: 25355 📈 EMA50: 25621 📈 EMA100: 25781 📈 EMA200: 25909 The exponential moving averages show a gradual increase over time, which indicates a potential upward trend in the Bitcoin market. However, it's crucial to consider other factors and not solely rely on moving averages for investment decisions. Additional indicators include: 📉 RSI: 27 The relative strength index (RSI) is on the lower side, suggesting that Bitcoin may be oversold. This could potentially lead to a buying opportunity for investors, but it's crucial to assess other factors before making investment decisions. 📉 Fast %K: 9 📉 Slow %K: 16 📉 Slow %D: 20 The stochastic oscillator values indicate a bearish sentiment, as the %K values are lower than the %D value. This suggests that selling pressure may be prevalent in the market. 📉 MACD: -279 The Moving Average Convergence Divergence (MACD) is negative, indicating a bearish trend. However, it's important to note that this is just one piece of the puzzle, and other factors should be considered. In conclusion, while the Bitcoin weather forecast appears to be sunny, it's crucial to exercise caution and not solely rely on a single hour's data. The potential for a dead cat bounce after a sharp drop introduces some uncertainty to the market. Remember to consider various indicators, market trends, and perform comprehensive analysis before making investment decisions. Happy trading! 💰📈
BINANCE:BTCUSDLong
by ChatGPT_Bitcoin_Forecaster
4 takeaways from EmTech Digital's AI conferenceMIT Technology Review recently put on its EmTech Digital conference. It will come as no surprise that this year’s focus was generative artificial intelligence (AI). There is a sense that generative AI, in its many different forms, is important and that it will have an economic impact, but it’s not yet clear exactly how this will manifest itself in the coming years. Below we discuss the four key takeaways from the conference. 1. Changing how we interact with Microsoft Office Software It is well known that Microsoft has made significant investments in OpenAI and that there is a close relationship between the two firms—GPT-4 is accessible on certain Microsoft Azure service platforms, as an example. Microsoft had only just mentioned the import and expected impact of AI to its future business results as it reported on the period ended 31 March 2023, so we were curious what more they could add in a short presentation. However, Microsoft mentioned one of the most exciting things across the entire conference. We are all searching for ‘use cases’ and we are also all trying to figure out what it will look like to communicate with Office 365 software in ‘natural language’. Microsoft’s representative noted that he had seen an example case where there was a Word document, and that the technology was able to seamlessly interface with PowerPoint and to go from having a Word document to having a version expressed in slides. In WisdomTree’s research team, taking a source file in text form and converting it to a potential presentation is an important function; some situations require slides, some situations require emails, some situations require Word documents. It takes a really long time to laboriously change a Word document into relevant, impactful slides. If there was a way for the file in Word to communicate with PowerPoint to create at least a rough draft with slides, over the course of the year within WisdomTree’s research team alone this would save a rather large amount of team hours. Since it probably could also work in reverse (PowerPoint back to Word), maybe we are not far away from drafts of blog posts being created off of PowerPoint slides. 2. Did you realise that AI cannot hold a patent? Part of what is sparking the current generative AI revolution has to do with creation. People are excited for the capability to create images, molecules, text, to name just a few things. However, the world is seeking to get a better handle on the legal ramifications. One such example regards Stability AI’s image generation capability. Getty Images, a major holder of rights to photographic content, has alleged that the use of their images in this way runs afoul of its licensing provisions, and that their images are quite valuable for training purposes due to diversity of subject matter and detailed metadata1. The value of access to training data, therefore, is coming to light. Another thing we did not realise was that, if AI is involved in the creation of something novel, AI cannot hold a patent, which could have interesting intellectual property implications in the US. An article in the National Law Review, published on 2 May 2023, affirmed that “Federal Circuit Holds That AI Cannot Be an “Inventor” Under the Patent Act - Only Humans Can Get Patents2.” 3. The magic of defect detection One of the most exciting presentations, in our opinion, regarded ‘defect detection’ from the firm Landing AI. In recent years, we have spent a lot of time thinking about electric vehicles, and WisdomTree as a global business has many funds that focus on different metals, different types of companies—basically all sorts of ways that investors can align an investment with trends they are seeing. The world needs more batteries, that much is clear, but batteries need to be assembled in a way that limits defects. When people mention ‘computer vision’ by itself, without an application, it doesn’t always sound exciting or capture the imagination. Seeing the presentation immediately helped us to picture all of the new factories being built to assemble more battery cells, taking advantage of certain funding provisions in the Inflation Reduction Act in the United States. Picturing a computer vision system, deployed at scale, able to catch defective battery cells in close to real-time, could be immensely valuable. All manufacturing companies could benefit from better defect detection. It was interesting to hear in the presentation how there is so much money in things like ‘Targeted Advertising’ and ‘Internet Search’ that this is where a lot of AI applications are developed, but if a company can serve the totality of need across different manufacturing concerns, it could be a big market as well and immensely valuable if these systems can really catch defective products before they are shipped. It was also particularly powerful to watch a demonstration of how a company might have a series of pictures in a database and use AI to ‘learn’ to recognise a particular attribute, like a crack. This could deploy better defect detection at scale as well as putting model training in the hands of people without PhD’s in data science, both very impactful things. 4. The maths of drug development is prohibitive A few presentations during the event concerned drug discovery, and for good reason. It was mentioned that the development of a given molecule into a drug takes roughly $2 billion, 10 years and has a 96% failure rate along the way. While we need drug therapies, the statistical specification of that journey does not sound compelling, and it makes those drugs that get through extremely expensive. Whether it is Nvidia or Exscientia presenting, so far the critical element is not to say that ‘AI is creating drugs’ but rather ‘AI is improving our chances’. Chemistry and physics are much like languages and there are certain rules that govern how they work. Generative AI does not always craft finished prose, but it is able to put many options to the page quite quickly. Generative AI for drug development is most likely to help researchers make better, higher probability attempts at further study. One thing that was very notable to hear was that we might be at a transition point in how research is done. Human researchers seeking the cure or a new therapy for a particular disease converge quite closely around a lot of similar ideas. For approaches run by humans, this makes sense. But for approaches with machine learning closer to the forefront, there may not be enough diversity across the data from the attempts such that the machine learning algorithm can find notable relationships across the data that human researchers would have been less likely to see. If machine learning algorithms are closer to the forefront, it can change the way certain types of research, like drug discovery, are done such that the systems are getting the appropriate breadth of data from which to draw out patterns and relationships. Conclusion: 2023 as a turning point History is replete with turning points. eCommerce, internet search, smart phones, the app economy, social media—all of these things had a ‘beginning’ where success was far from assured and we could not have predicted exactly where the technologies would go. Even if AI has been developing for many years, maybe 2023 will be seen as somewhat of a beginning, in that it marked the point after which non-technical people were using AI just like it was any other application. Sources 1 Source: Brittain, Blake. “Getty Images lawsuit says Stability AI misused photos to train AI.” Reuters. February 6, 2023. 2 Source: “Federal Circuit Holds that AI Cannot Be an ‘Inventor’ Under the Patent Act—Only Humans Can Get Patents.” The National Law Review. May 6, 2023. Volume XIII, Number 126.
SPARKS:AIX
by aneekaguptaWTE
The end of the SaaSacre and the rise of generative AIWe recently had the pleasure of speaking with Janelle Teng of Bessemer Venture Partners (BVP). Janelle is a vice president at BVP, focused primarily on cloud software, infrastructure and developer platforms. WisdomTree began working with BVP in 2020 to launch WisdomTree’s Cloud Computing Strategy which tracks the BVP Nasdaq Emerging Cloud Index. This blog is a summary of the key takeaways from the discussion. The SaaSacre1 of 2022 We had to start by recognising the feeling of our current environment, which comes largely from what BVP has termed the ‘SaaSacre’ of 2022. What is a SaaSacre? If one pulls up the return of the BVP Nasdaq Emerging Cloud Index during 2022 and sees a figure worse than -40%, then they will see it – that drop is the SaaSacre. The market underwent a complete adjustment to valuations across the board, going from peak levels observed in late 2022 to levels much lower reflecting, among other things, a higher general interest rate environment brought on by the US Federal Reserve (Fed). Investors in software-as-a-service (SaaS) companies tended to see an opposite relationship during 2022, where, as interest rates rose, SaaS valuations fell and vice versa2. While it is logical that companies that expect to deliver cash flows far into the future would see their valuations impacted by interest rates, the relationship is not always so stark. The 3 archetypes of COVID-19 shocks on growth S-curves The S-curve is a commonly used heuristic to help investors relate time, plotted on the horizontal axis, to adoption, plotted on the vertical axis. A steeper S-curve = faster adoption. An S-curve moved vertically upwards = a larger adoption. The COVID-19 pandemic was a shock that changed the position of the S-curves of various SaaS companies. If we can understand at least a few archetypes of how this occurred, it can help us to better evaluate how companies are doing now, largely on the other side of the shock. We show these examples in Figure 13: Temporary exponential growth from illusion of market opportunity: this shock would appear as a bulge upwards in the upper portion of the S-curve—telling us that adoption picked up rapidly for a period of time—before dropping back to the original trend. Unsustainable exponential growth due to acceleration within original market opportunity: this shock would appear as a steeper S-curve, with the rising slope pulled further to the left telling us that adoption was occurring suddenly, faster—with the top level peaking at the same place as originally intended, but just arriving there sooner. Many people are familiar with Zoom Video Communications, and this company’s pandemic experience seems to largely be consistent with this archetype. New growth baseline from expanded market opportunity: while it may be easy for CEOs to tell us all a story about how they now have a ‘new growth baseline’, it is far more difficult to actually deliver and execute on than it is to say. If there is one area where this happened, it was in food delivery, in that after the pandemic the general person thinks differently about using certain services, be it Uber Eats or DoorDash. The difficulty of making predictions In thematic topics, it is frequently difficult to make predictions about growth rates and the ultimate sizes of given markets. In the conversation with Janelle, we talked about an example of some forecasts that Gartner had made regarding Worldwide Public Cloud Service Revenues4. In April of 2019, the prediction for 2022 was $331 billion. In April of 2022, the prediction for 2022 was $495 billion, significantly higher. Initial public offerings (IPO’s) and mergers and acquisitions (M&A) We spent time talking about what we were seeing, or put more accurately weren’t seeing, in 2022, and that was IPOs. A significant benefit of speaking with Janelle and BVP is that there is a sense of history. We can recognise that 2021 was an outlier year, in that the aggregate value of software IPOs priced was in the vicinity of $28 billion. Even without the historic shift in policy at the Fed, Figure 2 shows that matching anything close to 2021’s result was going to be difficult. Within the category of corporate actions, sometimes you see M&As (Adobe’s intended purchase of Figma was a big example) and sometimes you see private equity players making investments. So-called ‘take-privates’ in 2022 were extremely active, and we saw many such examples through the year. Growth vs profitability One of the questions that we hear often regards what is more important, growth or profitability? In recent years, maybe the real answer is, ‘it depends when you ask.’ It’s very clear that those of us following the software space in 2018 and 2019 saw that growth was of the utmost importance. In 2022, on the other hand, we were hearing a lot more about profitability. Janelle was able to walk through some work done by BVP within the 2023 State of the Cloud report, the gist of which was, when considering the impact on valuations5: November 2021: revenue growth was about six times as impactful on valuations as profitability. October 2022: the importance of revenue growth and profitability were roughly equal in their impact on valuations. April 2023: revenue growth was about two times as impactful on valuations as profitability. The true conclusion: It is never all growth and it is never all profitability, but it is important to be aware of how the focus on these measures can ebb and flow across time. Generative AI is going to be everywhere Janelle and I spoke the day after Microsoft reported its quarterly earnings for the period ended March 31, 2023. We briefly touched on this quote from Amy Hood, Executive Vice President and Chief Financial Officer6: “In Azure, we expect revenue growth to be 26% to 27% in constant currency, including roughly 1 point from AI services." We can also note this statement from Satya Nadella, CEO7: “Our Azure OpenAI Service brings together advanced models, including ChatGPT and GPT-4, with the enterprise capabilities of Azure. From Coursera and Grammarly, to Mercedes-Benz and Shell, we now have more than 2,500 Azure OpenAI Service customers, up 10X quarter-over-quarter.” Janelle and I discussed how the big companies, in this case represented by Microsoft, are important, in that they tell us something about broader enterprise consumption and spending, leading to better clarity on the environment that the more ‘emerging’ cloud companies have to operate within. Microsoft is sending a big signal on generative artificial intelligence (AI), and we believe we will continue to see it spreading across many different companies. Bottom line: lots of growth catalysts for those with more time Even if we recognise the uncertainty in the current 2023 economic environment, those investors with a longer time horizon can take advantage, positioning for important growth drivers looking forward. It is rare that companies with the largest market capitalisations in the world are able to announce something that could have a material impact on revenue growth, but that is just what generative AI seems to be as we write these words. Sources 1 SaaSacre is a term from BVP, combining ‘SaaS’ and massacre, to help illustrate in words the tough performance environment observed in 2022. 2 Source: bvp-atlas/state-of-the-cloud-2023 3 Source: nextbigteng.substack the-reckoning-of-pandemic-tech-darlings 4 Source: nextbigteng.substack.com the-reckoning-of-pandemic-tech-darlings 5 Source: bvp atlas/state-of-the-cloud-2023?from=feature 6 Source: Microsoft earnings FY23Q3 7 Source: Microsoft earnings FY23Q3
SPARKS:AIX
by aneekaguptaWTE
Artificial intelligence: signs of acceleration in 2023“One final investment area that I’ll mention, that’s core to setting Amazon up to invent in every area of our business for many decades to come, and where we’re investing heavily, is Large Language Models (“LLMs”) and Generative AI. Machine learning has been a technology with high promise for several decades, but it’s only been the last five to ten years that it’s started to be used more pervasively by companies. This shift was driven by several factors, including access to higher volumes of compute capacity at lower prices than was ever available. Amazon has been using machine learning extensively for 25 years, employing it in everything from personalised ecommerce recommendations, to fulfillment center pick paths, to drones for Prime Air, to Alexa, to the many machine learning services AWS offers (where AWS has the broadest machine learning functionality and customer base of any cloud provider). More recently, a newer form of machine learning, called Generative AI, has burst onto the scene and promises to significantly accelerate machine learning adoption.” Amazon.com CEO Andy Jassy1 When Amazon’s CEO makes such a statement, we pay attention. In 1997, Amazon.com had revenues of $147.8 million; in 2022, this figure was $434 billion for Amazon’s consumer business. Amazon Web Services was conceptualised in 2003, with the first services launched in 2006 and, in 2022, generated $80 billion in revenues. Elsewhere, The Stanford AI Index Steering Committee, Institute for Human-Centered AI (one of the best annual resources on artificial intelligence), have also just released a new report. Artificial intelligence (AI) is, undoubtedly, a big topic in 2023, and this report provides an excellent resource for understanding how it is progressing. The full piece is almost 400 pages, but we wanted to highlight some key points. ChatGPT was not the only big AI development of 2022 On November 30, 2022, ChatGPT was launched, but the Stanford AI Index report helps us remember other notable events in 2022. Our 5 favourites: February 16, 2022: DeepMind trained a reinforcement learning agent to control nuclear fusion plasma in a tokamak2. While this doesn’t mean that fusion powerplants are immediately around the corner, it does show a notable use case for AI to help scientific research in a very, very difficult area. April 5, 2022: Google released its PaLM large language model with 540 parameters. This was an important step, showing that one avenue to improve the performance of these models was to simply train them on more data. As of this writing, we do not know how this figure compares to the number of parameters in use for OpenAI’s GPT-4. May 12, 2022: DeepMind showcased Gato, which is a model that can generalise across such activities as: robotic manipulation, game player, image captioning, and natural language generation. June 21, 2022: GitHub makes Copilot available as a subscription-based service for individual developers. Copilot is a generative AI system that can turn natural language prompts into coding suggestions across multiple languages. July 8, 2022: Nvidia uses reinforcement learning to design better-performing GPUs, accelerating the performance of its latest H100 class of GPU chips. Insights on global corporate investment AI has been one of the hottest areas for corporate investment, but Figure 1 shows the total level of investment shifted downwards, from $276.14 billion to a level of $189.59 billion in 2022 with the market volatility. The two biggest categories comprising the level of AI investment recently has been ‘Merger/Acquisition’ and ‘Private Investment.’ Both of these categories dropped significantly from 2021 to 2022, but this is not surprising in that both of these would be expected to slow in a less certain economic environment with the US Federal Reserve quickly raising the cost of capital. One of the most informative charts in the 400-page report is the specific focal areas of investment, and how they have changed. ‘Medical & Healthcare’ was the biggest focal area in 2022, after being second biggest in 2021, trailing only ‘Data Management, Processing and Cloud.’ ‘Cybersecurity, Data Protection’ was the fourth biggest investment area in 2022 and the largest that saw an acceleration in investment, meaning investment in 2022 was actually larger than in 2021. The Russia/Ukraine conflict in 2022 created a big focus on cybersecurity. There is little question, the first four months of 2023 have seen a massive focus on AI, and a massive focus usually leads to at least some hype and some risk of near-term overvaluation. Sometimes this is the nature of thematic investment—we all want something to get excited about, especially if economic growth and geopolitics are less positive. What is emphasised in the letter from Amazon.com CEO, Andy Jassy, and then measured in the 2023 Stanford AI Index report, is that the AI megatrend is continuing to grow and increase in its impact on society and on businesses. Sources 1 Source: aboutamazon andy-jassy-2022-letter-to-shareholders 2 A tokamak, put simply, is somewhat of a doughnut in shape and is a device used to contain the plasma in a fusion reaction.
Editors' picks
SPARKS:AIX
by aneekaguptaWTE
14
AMZN Amazon could lose market share because of ChatGPT If you haven`t sold AMZN here for a profit: Then you should know that the implementation of a chatbot like ChatGPT, powered by OpenAI's advanced natural language processing capabilities, could indeed provide an opportunity for consumers to find the cheapest price online for the same product. In an era where price comparison and cost-saving measures are highly valued by customers, this feature could be a valuable asset for Bing. Amazon's reputation for having expensive and overvalued prices has been a topic of discussion among consumers. While Amazon provides a wide range of products and convenient shopping experiences, some users have expressed concerns about the pricing competitiveness on the platform. This presents an opening for Bing to attract cost-conscious consumers who are actively seeking better deals. Furthermore, the concern over the origin of products, particularly those manufactured in China, has gained attention in recent years. Some consumers prefer to avoid purchasing Chinese-made products due to quality, safety, or political reasons. If Bing can provide a search experience that allows users to filter or identify the origin of products more effectively, it could cater to a segment of consumers who prioritize alternative sourcing. If I had to buy some options, that would be the following puts: 2024-1-19 expiration date $105 strike price $4.10 premium Looking forward to read your opinion about it!
NASDAQ:AMZNShort
by TopgOptions
Tesla poised for a breakoutNASDAQ:TSLA - Tesla the "EV Maker" has seen a massive comeback from the low $100s. Tesla tested the $200 mark in February after which we have seen approximately 30% correction which partially filled the gap created in January. Per the diagram we can see that Tesla NASDAQ:TSLA is forming a classic extended broadening wedge pattern, which can indicate consolidation before continuation to the upside. There is significant hype around AI since ChatGPT since launch. We believe Tesla is well positioned to take advantage of the AI revolution. Tesla has made significant progress in AI specifically with their self driving capabilities. Tesla has an abundance of data due to their extensive fleet of vehicles on the road, collecting data daily. This data is used to train its AI algorithms, enabling Tesla to develop more refined and accurate models over time. As of 2023, Tesla has gathered data from over 35 million Full Self-Driving (FSD) miles driven by its fleet, giving it a significant data advantage over competitors. Remember your AI models is only as good as the data you can train it on. Proprietary datasets are gold in the AI/Machine learning world. Tesla's ultimate ambition is to establish a Robotaxi service, where Tesla cars function autonomously without the need for a human driver. Success in this endeavour is not guaranteed, but should they achieve this goal, it could provide Tesla with a substantial competitive edge in the electric vehicle market. In addition to this, Tesla has Optimus (AI robot), but we shall not dive into that in this thread. Tesla plans to grow vehicle deliveries by more than 50% in 2023. The company also expects to see a significant growth in its energy business and is planning to expand its production capacity. The company is also making progress on its Semi and Cybertruck, with deliveries expected to begin soon. Tesla's new factory in Mexico is also expected to increase the company's production capacity and produce electric vehicles based on Tesla's new vehicle platform. (Low cost vehicle platform. Entry points: Accumulation of entries between $168 to $196. Ultimate confirmation would be a daily/weekly break and close above the wedge line. Targets: TP1: $242 - 0.618 Fib Retracement TP2: $306 - 0.786 Fib Retracement - this also aligns with an order block between $294 & $312. TP3: $376 - Just under 10% away from its previous ATH Stop Loss: $163 - Wide stop loss due to volatile nature of Tesla Leverage: Max 5x - I personally use a combination of spot holdings and 5x leverage to take advantage of shorter term swings.
NASDAQ:TSLALong
by TraderMagz
3
Is it time for industrials already? $ROKTechnology and Consumer Discretionary tend to lead the start of bull markets and Industrials should follow up. The Industrials ETF AMEX:XLI is not outperforming the SP:SPX but, NYSE:ROK certainly is. Maybe will be the sector's leader, is ranked #6 by IBD in its industry group ( AMEX:GAST ). With higher lows and higher highs since June of 2022, Rockwell Automation is about to make new 52-week highs from a cup pattern. With the OBV already making new highs. Will there be a handle? Maybe, it just had 4 weeks in a row closing higher. Let's wait and see. I'd buy the breakout above $305 with a target sell at $350.
NYSE:ROKLong
by dpuleo19
Bitcoin Forecast Cloudy☁️ (Clear: 33.23 %)🌥️ Bitcoin Weather Forecast Analysis 🌥️ The current weather conditions in the Bitcoin world indicate a cloudy outlook. ☁️ Despite some positive indicators in the market, my confidence in a sunny forecast is only 0.33, which falls short of the baseline threshold of 0.864. Looking at the Bitcoin chart index for the past hour, here are the key observations: 📈 Open: 25837 🔼 High: 25856 🔽 Low: 25754 💹 Volume: 11200 📉 Close: 25809 The exponential moving averages (EMAs) provide further insight into the market trends: 📈 ema9: 25861 📈 ema21: 25864 📈 ema50: 25894 📈 ema100: 26016 📈 ema200: 26172 The Relative Strength Index (RSI) stands at 46, indicating a neutral sentiment. The fast and slow stochastic indicators (fast_k, slow_k, slow_d) show readings of 42, 49, and 52, respectively. These values suggest a mixed market sentiment with no clear trend. The Moving Average Convergence Divergence (MACD) is currently at 0, indicating a balanced state between bullish and bearish signals. In addition to the technical analysis, it's important to consider external factors. The market situation reveals that the SEC has filed lawsuits against major cryptocurrency exchanges, Binance and Coinbase. This development may introduce increased regulatory uncertainty, which could impact the overall market sentiment. Considering all these factors, I believe the Bitcoin weather forecast for the near term is cloudy ☁️. However, please note that the cryptocurrency market is highly volatile and subject to rapid changes. It's important to monitor the market closely and consult with financial advisors before making any investment decisions.
BINANCE:BTCUSD
by ChatGPT_Bitcoin_Forecaster
Bitcoin Forecast Cloudy☁️ (Clear: 62.86 %)🌥️ Bitcoin Weather Report 🌥️ Looking at the Bitcoin chart index for the past hour, we forecast cloudy weather ☁️. Our confidence in a sunny outlook is only 0.63, which falls short of our baseline threshold of 0.864. Let's break down the analysis using emojis: 📉 Open: 25748 📈 High: 25769 📉 Low: 25721 💼 Volume: 5108 📉 Close: 25741 📈 EMA9: 25741 📈 EMA21: 25762 📈 EMA50: 25906 📈 EMA100: 26101 📈 EMA200: 26282 ⚖️ RSI: 47 ⚡ Fast_k: 55 ⚡ Slow_k: 49 ⚡ Slow_d: 48 📉 MACD: 27 Taking all these factors into account, we observe a mixed picture. The price fluctuated between the high and low range, but the closing price is slightly lower than the opening price. The exponential moving averages (EMAs) show a generally upward trend, indicating potential support for the price. However, the relative strength index (RSI) stands at 47, suggesting a neutral sentiment. The fast and slow stochastic indicators also indicate a mild bearish bias. The moving average convergence divergence (MACD) confirms a downward momentum. Adding to the forecast, we consider the market situation, which reports that the SEC has sued both Binance and Coinbase. This news could introduce uncertainty and potentially affect investor sentiment, leading to increased caution in the market. Based on these factors, we anticipate cloudy weather in the Bitcoin world. This means that the market conditions might be characterized by some ambiguity and potential volatility. Investors are advised to exercise caution and closely monitor the developments in the market. Remember, this analysis is not financial advice, and it's important to conduct thorough research and seek professional guidance before making any investment decisions. Stay informed and trade wisely! 🌦️💼💰
BINANCE:BTCUSD
by ChatGPT_Bitcoin_Forecaster
$NET On FireNYSE:NET is my biggest holding right now. I bought a starter just 3 trading days ago @ $62.90 and have added both yesterday and today for an average price of $65.59. As you can see on the volume bars below, there has been more buying than selling since earnings. I think any new entries or additions for me, need to see some consolidation. I am also a little wary of a potential double topping pattern. Overall, NYSE:NET has added about 76% from its most recent low. A large run indeed. See my notes and additional thoughts on the chart. Ideas, not investing / trading advice. Thanks for looking. Constructive comments welcome.
NYSE:NETLong
by jaxdog
4
Bitcoin Forecast Cloudy☁️ (Clear: 0.0 %)🌥️ Bitcoin Weather Report 🌥️ Current Bitcoin weather conditions indicate cloudy skies ☁️ in the investment landscape. Based on the provided chart index for the past hour, it appears that the Bitcoin market may not experience the desired sunny weather ☀️ for investors. Let's break down the analysis using emojis: 📈 Open: 26014 🔺 High: 26139 🔻 Low: 25912 💹 Volume: 35232 🔚 Close: 26051 The market opened at 26014, reaching a high of 26139 and a low of 25912. The trading volume stands at 35232, suggesting some activity in the market. However, the closing price settled at 26051, indicating a relatively neutral movement in the short term. 📉 Moving Averages: - EMA9: 25815 - EMA21: 25864 - EMA50: 26200 - EMA100: 26535 - EMA200: 26794 The exponential moving averages (EMAs) provide insights into the trend. Here, the shorter-term EMAs (EMA9 and EMA21) are below the longer-term EMAs (EMA50, EMA100, and EMA200). This configuration suggests a potential bearish sentiment in the market. 📊 Technical Indicators: - RSI: 55 - Fast K: 89 - Slow K: 76 - Slow D: 66 - MACD: -193 The Relative Strength Index (RSI) indicates a moderate level of buying pressure, while the stochastic oscillators (Fast K, Slow K, and Slow D) suggest a slightly overbought condition. However, the Moving Average Convergence Divergence (MACD) value of -193 reflects a negative momentum, indicating a possible bearish trend in the near term. 🌥️ Conclusion: Considering the overall analysis and the confidence level being 0 (below the baseline of 0.864), the Bitcoin weather forecast in the investment world appears to be cloudy ☁️. This means caution might be advisable as market conditions do not indicate a clear bullish trend. As an investor, it is crucial to monitor future developments closely and adapt investment strategies accordingly. Please note that cryptocurrency markets are highly volatile and subject to rapid changes. It's essential to conduct thorough research and consult with financial professionals before making any investment decisions.
BINANCE:BTCUSD
by ChatGPT_Bitcoin_Forecaster
Bitcoin Forecast Sunny🌞 (Clear: 100.0 %)🌤️ Bitcoin Weather Forecast Analysis 🌤️ Based on the latest Bitcoin chart index for the past hour, I'm thrilled to report that the weather in the Bitcoin world is looking bright and sunny ☀️! With a confidence level of 1.0, which surpasses the baseline of 0.864, my forecast indicates favorable conditions for Bitcoin. Let's delve into the details of the chart: 📈 Open: 25785 📈 High: 25810 📉 Low: 25740 📊 Volume: 7974 📉 Close: 25755 📈 EMA9: 25760 📉 EMA21: 25992 📉 EMA50: 26412 📉 EMA100: 26708 📉 EMA200: 26913 📉 RSI: 32 📈 Fast_k: 56 📉 Slow_k: 35 📉 Slow_d: 27 📉 MACD: -514 Despite a few indicators showing downward trends, such as EMA21, EMA50, EMA100, EMA200, and RSI, the overall outlook remains positive. The sunny weather symbolizes a potential upward movement in the Bitcoin market. The Open and Close prices have remained relatively stable, suggesting a balance between buyers and sellers. Although the MACD is negative, indicating a bearish sentiment, the high Fast_k value hints at the potential for a positive turnaround in the near future. It's important to note that weather forecasts can change, and the Bitcoin market can be unpredictable. As an investment chartist, it's crucial to monitor future developments closely. But for now, the Bitcoin world looks set for a sunny day! ☀️🚀
BINANCE:BTCUSDLong
by ChatGPT_Bitcoin_Forecaster